Staff Data Scientist, Product
Summary
Staff Data Scientist serving as technical lead for Fetch's off-platform data business: building predictive audience models, relevance/ranking, and causal-inference ad measurement systems from prototype to production. Hands-on with Python, SQL, Snowflake, and dbt while mentoring a small team of data scientists.
- Lead a small team of data scientists as technical lead, owning the quality and delivery of the team's work.
- Set the technical direction and roadmap across audiences, measurement, and data feeds, partnering with product and engineering on the design, quality, and coverage of the data delivered to partners.
- Architect and build the models and systems behind our data products.
- Develop data scientists in causal inference, predictive modeling, and clear communication.
- Build predictive models that identify likely buyers and extend audiences beyond Fetch's user base.
- Shape relevance and ranking approaches that match the right audiences to advertiser goals.
- Define how audience quality is evaluated and articulate what differentiates Fetch audiences in a crowded market.
- Extend these models to in-product use cases, such as acquiring high-value users for Fetch.
- Own the measurement frameworks that connect ad exposure to verified conversions using Fetch data, and turn one-off analyses into repeatable, scalable products.
- Drive the application of causal inference and experimental design to establish whether advertising drove outcomes.
- Champion our methodology with customers, partners, and industry leaders, anticipating the challenges they will raise.
- Establish our approach as a trusted market standard through clear documentation and evangelism.
- Align senior leaders around clear, decisive recommendations on strategy and tradeoffs.
- Develop strong partnerships across product, engineering, and Go-to-Market teams, including sales and business development.
- Carry work from prototype to production alongside ML engineering, data engineering, and platform teams.
- Spot gaps others haven't, build alignment across stakeholders, and sustain momentum on long-running initiatives.
- 8+ years of total experience in data science or applied statistics, including 3+ years of industry experience building ads platform capabilities, such as audience products or measurement systems.
- Strong statistical foundation, with deep expertise in causal inference and advertising measurement.
- Hands-on experience building and architecting predictive modeling systems for advertising as well as relevance and ranking systems.
- Experience building systems that run beyond a prototype, with the ability to partner with engineering to take them into production.
- Experience leading or mentoring other data scientists, including setting technical direction and reviewing the quality of their work.
- Experience leveraging modern analytics tooling such as Python, SQL, Snowflake, and dbt.
- A clear track record of influencing senior leadership and partnering with product and engineering stakeholders.
- Clear and decisive written and verbal communication, including the ability to explain complex methodology to non-technical audiences.
- Demonstrated initiative in identifying problems others haven’t and driving them to resolution across teams.
- Demonstrated ability to evaluate AI tools critically and apply them where they meaningfully improve results.
- Bachelor’s degree in a quantitative field.
- Advanced degree in a quantitative discipline.
- Experience with off-platform and programmatic advertising or identity.
- Experience defending measurement or audience methodology in conversations with external customers or industry partners.
- Experience partnering with GTM, sales, or business development teams.
- Experience with retail or CPG purchase data.
- Reviewing and organizing applications and resumes to help our recruiting team manage high volumes of submissions, including automated review of fraud signals to identify bad actors;
- Identifying candidates whose stated qualifications and experience appear relevant to an open position;
- Scheduling and coordinating interviews with candidates;
- Generating interview summaries or notes to assist recruiters and hiring managers in their review; and
- Conducting research on open roles and candidate pools to improve the effectiveness of our recruiting practices.
SoftBank Vision Fund 



